Field of the Invention
The present invention relates to a device and a method for determining the position of an instrument in relation to medical images.
Description of Related Art
Navigation systems are commonly tracking instrument position and orientation with respect to medical images of a body. Conventional tracking devices are made of optical devices, magnetic devices, ultrasonic devices, inclinometers, and accelerometers, radio-frequency measurement devices, used independently or in combination. In optical systems, tracking the position of an instrument is usually achieved by placing emitters or reflectors on both the instrument and on the body reference and observing the scene with two or three cameras. The most widely used system is the Polaris device manufactured by the company Northern Digital Inc; (Waterloo, Ontario, Canada). Existing optical localization devices are expensive and cumbersome, or not accurate enough.
Magnetic localization devices such as Aurora from the company Northern Digital Inc. (Waterloo, Ontario Canada) are compact but they are expensive; in addition, they require special care in environments with the presence of metallic objects such as the examination table or magnetic objects that constitute the core of magnetic resonance imaging devices, which may lead to inaccurate measurements.
Coming back to optical systems, video images can be used to detect the position and orientations of different types of objects, using one camera, or two cameras in stereoscopic systems, or even multiple cameras to add accuracy and robustness to measurements. In particular, in U.S. Pat. No. 7,876,942 from Gilboa, one or several micro-cameras are rigidly fixed to a needle wherein the micro-cameras observe at the same time the needle and a calibration target that is used as a reference phantom mounted on a body, said reference phantom being visible on medical images of the body. But this device requires equipping a needle with cameras which adds weight to the needle and that operators do not appreciate. In addition, if a micro-camera is mounted on a needle, the positions of the fingers and hands must be such to avoid the occlusions of the reference phantom, which adds complexity instead of providing a simple assistance to the operator. This is not a fluid process.
There is therefore a need for a method and device that can track the position of an instrument with respect to medical images of a body that is very easy to use with low constraints and that can be used in environments with metallic or magnetic objects.
Algorithms to detect and locate in three dimensions an object made of points and lines, or objects with a known geometry, or hands and fingers, from one or several video images have been developed for many years in the literature of computer vision and many variations exist. This is often referred to as stereoscopic measurements and detection although three or more cameras can be used instead of two. The theory of computer vision with only one camera is also well known and falls in the category of stereoscopy. One can refer for example to the basic principles exposed in “D. P. Huttenlocher and S. Ullman. Recognizing Solid Objects by Alignment with an Image. International Journal of Computer Vision, 5(2):195-212, 1990” or in “G. Borgefors. Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10(6):849-865, 1988” or in “S. Lavallée and R. Szeliski. Recovering the position and orientation of free-form objects from image contours using 3-D distance maps. IEEE PAMI (Pattern Analysis and Machine Intelligence), 17(4):378-390, 1995” or in the textbook “R. Szeliski. Computer Vision: Algorithms and Applications, Springer, Texts in Computer Science, 2011”. Several standard packages are also available for using common computer vision algorithms such as for instance “The Machine Vision Toolbox” which is available on the web site http://www.ict.csiro.au/downloads.
For example, a package for automatic calibration of video cameras using calibration grids is available on: http://www.vision.caltech.edu/bouqueti/calib doc/htmls/example.html or also in http://www.vision.ee.ethz.ch/software/calibration toolbox//calibration toolbox.php. However, those algorithms provide basic tools and components that any system in computer vision uses commonly, but they fail to provide a solution to the specific problem mentioned above.